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Optimizing Beat Management System Using Soft Biometrics

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Advanced Computing (IACC 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1781))

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Abstract

In the Police Department, officials need to carry out regular beats in prescribed areas and monitor their attendance in real time. Marking attendance regularly at appropriate beat location at a prescribed time becomes challenging. The motive of the paper is to implement a Beat Management System using the deep metric learning algorithm for the Police Department to collaborate with the community within the assigned territory. The Deep metric learning algorithm in facial recognition systems does an excellent job in addressing the nonlinearity and scalability in comparison to the conventional algorithms. A novel solution is proposed in the form of an end-to-end application in order to overcome the challenges faced by the Police Department in registering attendance. This serves as a concrete solution to the problem with the amount of data that can be generated in the form of facial images from Police Officers along with the precision-based geolocation tracking. The result obtained shows that the model supports even smaller sample sizes of 4–5 images of everyone. Incremental dataset uses the concept of self- learning in order to train the model on more images captured, analyzed and processed continuously in real time. The system recognizes the person by matching the features with an accuracy of 99.38% for a constrained sample size.

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Acknowledgment

The work is done in real time to assist the Beat Management at Tumkur region. We are thankful to Rudraradhya P, Managing Director, CEDLabs Pvt Ltd, Tumkur for the support and technical guidance in carrying out the work. We are thankful for the support of TEQIP-III, BMS college of Engineering, ISE Research Center for sponsoring the environment to carry out the research work.

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Authors and Affiliations

  1. Department of ISE, BMS College of Engineering, Bangalore, India

    N. Kaushik, Chandrakala G. Raju, Ishaan Joshi, M. Indramma & K. R. Radhika

  2. Department of CSE, Siddaganga Institute of Technology, Tumkur, India

    Sumalatha Aradhya

Authors
  1. N. Kaushik
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  2. Chandrakala G. Raju
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  3. Sumalatha Aradhya
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  4. Ishaan Joshi
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  5. M. Indramma
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  6. K. R. Radhika
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Corresponding author

Correspondence to N. Kaushik .

Editor information

Editors and Affiliations

  1. Bennett University, Greater Noida, India

    Deepak Garg

  2. CMR College of Engineering & Technology, Hyderabad, India

    V. A. Narayana

  3. Nanyang Technological University, Singapore, Singapore

    P. N. Suganthan

  4. Ramon Llull University, Barcelona, Spain

    Jaume Anguera

  5. CMR College of Engineering & Technology, Hyderabad, India

    Vijaya Kumar Koppula

  6. Bennett University, Greater Noida, India

    Suneet Kumar Gupta

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Kaushik, N., Raju, C.G., Aradhya, S., Joshi, I., Indramma, M., Radhika, K.R. (2023). Optimizing Beat Management System Using Soft Biometrics. In: Garg, D., Narayana, V.A., Suganthan, P.N., Anguera, J., Koppula, V.K., Gupta, S.K. (eds) Advanced Computing. IACC 2022. Communications in Computer and Information Science, vol 1781. Springer, Cham. https://doi.org/10.1007/978-3-031-35641-4_20

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  • DOI: https://doi.org/10.1007/978-3-031-35641-4_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35640-7

  • Online ISBN: 978-3-031-35641-4

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